• Corpus ID: 235727597

Towards Machine Learning-Based Meta-Studies: Applications to Cosmological Parameters

@inproceedings{Crossland2021TowardsML,
  title={Towards Machine Learning-Based Meta-Studies: Applications to Cosmological Parameters},
  author={Tom Crossland and Pontus Stenetorp and Daisuke Kawata and Sebastian Riedel and Thomas D. Kitching and Anurag C. Deshpande and Tom Kimpson and Choong Ling Liew-Cain and Christian Pedersen and Davide Piras and Monu Sharma},
  year={2021}
}
We develop a new model for automatic extraction of reported measurement values from the astrophysical literature, utilising modern Natural Language Processing techniques. We use this model to extract measurements present in the abstracts of the approximately 248,000 astrophysics articles from the arXiv repository, yielding a database containing over 231,000 astrophysical numerical measurements. Furthermore, we present an online interface (Numerical Atlas) to allow users to query and explore… 

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Bidirectional Attention Flow for Machine Comprehension

TLDR
The BIDAF network is introduced, a multi-stage hierarchical process that represents the context at different levels of granularity and uses bi-directional attention flow mechanism to obtain a query-aware context representation without early summarization.

of the Association for Computational Linguistics: